Methods
Network Analysis in Finance and Economics
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Duration
28/03/2022 - 13/04/2022
Early Bird
-10% before 15 February
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Level
Intermediate
Approach
Quantitative
Delivery mode
Online
Over the last years, network analysis has become an active topic of research, with numerous applications in macroeconomics and finance. In a nutshell, network analysis is concerned with representing the interconnections of a large panel as a graph: the vertices of the graph represent the variables in the panel, and the presence of an edge between two vertices denotes the presence of some appropriate measure of dependence between the two variables. Dependence can derive from direct exposures or from indirect or common exposures. From an economic perspective, the interest on networks has been boosted by the research of, inter alia, Acemoglu et al. (2012), which shows that individual entities can have a non-negligible effect on the aggregate behaviour of the economy when the system has a high degree of interconnectedness. Especially since the 2008 global financial crisis, the interest in analysing the role of network structure in transmitting – or dissipating – stress has grown significantly.
In this course, participants will be introduced to the theoretical framework and literature behind network analysis techniques for applications in finance and economics. Practical application of the methodologies will be presented in the form of examples, case studies and exercises. These sessions will be supported by code written in Python, with some parts available also in R.
I found this course extremely useful and well done! I learnt a lot and I am looking forward to put into practice the knowledge I acquired.
Participant in the 2021 edition of the course
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Jan Trevisan
Head of online training team
Online Training Officer
Robert Schuman Centre for Advanced Studies
